Presented By O'Reilly and Cloudera
Make Data Work
September 25–26, 2017: Training
September 26–28, 2017: Tutorials & Conference
New York, NY

The journey to Einstein: Building a multitenancy AI platform that powers hundreds of thousands of businesses

Simon Chan (Salesforce)
2:55pm3:35pm Wednesday, September 27, 2017
Data Engineering & Architecture, Enterprise adoption
Location: 1A 23/24 Level: Beginner
Secondary topics:  Platform, Sales
Average rating: *****
(5.00, 1 rating)

Who is this presentation for?

  • Data scientists and developers

Prerequisite knowledge

  • Experience using AI applications

What you'll learn

  • Learn how Salesforce enables AI development on production at scale for all its business lines, for both internal and external developers
  • Discover the challenges and solutions to apply AI in multitenant cloud businesses

Description

Artificial intelligence is a game changer that’s transforming the very foundation of how businesses interact with customers. Salesforce is bringing AI to every business through its comprehensive set of business lines, such as sales, service, marketing, commerce, community, analytics, and the IoT.

Salesforce recently released Einstein, which brings AI into its core platform to power every business. In addition to enabling prebuilt predictive applications, Einstein empowers customers to quickly build AI-powered apps that include Einstein-powered fields in any object, page layout, or workflow, making every business process smarter. For data scientists and developers, Einstein offers predictive vision and sentiment services that enable developers to train deep learning models to recognize and classify images and sentiment in text. And PredictionIO in Heroku Private Spaces empowers developers to build custom machine learning models and put them into their apps.

The secret behind Einstein is an underlying platform that accelerates AI development at scale for both internal and external data scientists. Simon Chan shares his experience building this unified AI platform to power advanced machine learning, deep learning, natural language processing, and smart data discovery for multiple enterprise product lines. Simon discusses the challenges involved in enabling ML models to be automatically customized for every single customer in a multitenancy cloud business and handling various technologies employed by different teams, such as SparkML and TensorFlow, before leading a deep dive into the cross-cloud data platform architecture. Along the way, he shares best practices for building an AI platform for large-scale production deployment.

Photo of Simon Chan

Simon Chan

Salesforce

Simon Chan is a senior director of product management for Salesforce Einstein, where he oversees platform development and delivers products that empower everyone to build smarter apps with Salesforce. Simon is a product innovator and serial entrepreneur with more than 14 years of global technology management experience in London, Hong Kong, Guangzhou, Beijing, and the Bay Area. Previously, Simon was the cofounder and CEO of PredictionIO, a leading open source machine learning server (acquired by Salesforce). Simon holds a BSE in computer science from the University of Michigan, Ann Arbor, and a PhD in machine learning from University College London.